Acta Poloniae Pharmaceutica ñ Drug Research, Vol. 68 No. 2 pp. 191ñ204, 2011
ISSN 0001-6837
Polish Pharmaceutical Society
DRUG SYNTHESIS
SYNTHESIS, ANTIMICROBIAL EVALUATION, QSAR AND IN SILICO
ADMET STUDIES OF DECANOIC ACID DERIVATIVES
ASHWANI KUMAR*1, SURENDER SINGH1, SANDEEP JAIN1 and PARVIN KUMAR2
1
Drug Discovery and Research Laboratory, Department of Pharmaceutical Sciences, Guru Jambheshwar
University of Science and Technology, Hisar-125 001, India
2
Department of Chemistry, Kurukshetra University,Kurukshetra, India
Abstract: Various derivatives of decanoic acid (CD) have been synthesized and evaluated against Gram positive B. subtilis, S. aureus and Gram negative E. coli bacteria as well as against fungi C. albicans and A. niger.
Quantitative structure activity relationship (QSAR) models for antimicrobial activities were developed using
multiple linear regression and cross validated by leave one out (LOO) approach. QSAR studies indicated that
activity against Gram positive bacteria was governed by lipophilicity of the compounds while topological steric
nature of the molecule was deciding factor for antifungal activity. Further, in silico ADMET studies showed
that compounds CD12, 19, 20 and 23 could be explored further for other activities.
Keywords: decanoic acid derivatives, antibacterial activity, antifungal activity, QSAR, in silico ADMET
toxicity (ADMET) characteristics. Since a tremendous amount of efforts has gone into finding bioactive molecule, ADMET are often the rate limiting
factor in drug discovery programme (8). In silico
ADME properties are expected to reduce the risk of
late stage attrition of drug development and to optimize screening and testing by looking at only the
promising molecules (9).
In view of the above, QSAR analysis of various decanoic acid derivatives with their antimicrobial activity is presented here. Further in silico
ADMET studies have been discussed.
Decanoic acid (capric acid) has been found to
have excellent antibacterial (1) and antifungal (2)
activities and its esters have been used in medical,
nutritional and dietetic fields. The mono and diglycerides of it acts as cholesterol dissolving agents in
treatment of patients having cholesterol gallstones,
due to the unique solvency properties of such
monoesters (3). Decanoic acid is potentially useful
product for reducing the level of colonization of
chicks and could ultimately aid in the reduction of
the number of contaminated eggs in the food supply
(4). Decanoic acid has also been successfully used
as oral absorption enhancer of insulin (5).
Quantitative structure activity relationship
(QSAR) attempts to find consistent relationships
between the variations in the values of molecular
properties and the biological activity for a series of
compounds, so that these rules can be used to evaluate new chemical entities (6). QSAR is widely used
in design of antimicrobial agents. In vitro antimicrobial studies of esters of substituted pyrazinoic acid,
which have 100 times more activity than pyrazinamide against Mycobacterium tuberculosis, have
been discussed using QSAR (7).
Once sufficient efficacy is obtained, the success or failure of a potential drug depends on its
absorption, distribution, metabolism, excretion and
RESULTS AND DISCUSSION
The ester derivatives of decanoic acid were
prepared by reaction of decanoic acid with corresponding alcohol in the presence of sulfuric acid.
Synthesis of amides was carried out by the reaction
of decanoyl chloride with corresponding amine
under cold and normal conditions (Scheme 1). The
physicochemical properties and molecular structures of various synthesized derivatives are given in
Table 1. The IR and NMR spectra of all derivatives
are recorded and interpreted thoroughly. All spectra
are in accordance with molecular structure of the
synthesized compounds. All the synthesized deriva-
* Corresponding author: e-mail: [email protected], phone: +91-94662-80487; fax: +91-1662-276240
191
192
ASHWANI KUMAR et al.
tives of decanoic acid are evaluated for their in vitro
antimicrobial activity against Gram positive bacteria, S. aureus, B. subtilis, Gram negative E. coli and
fungus, C. albicans and A. niger by standard serial
dilution method (10). Double strength nutrient broth
IP and Sabouraud dextrose broth IP (11) have been
used as media for growth of bacterial and fungal
cells, respectively. The results for antimicrobial
studies are presented in Table 2. Screening of this
table shows that derivatives are more effective
against Gram negative bacteria than Gram positive.
For Gram positive bacteria, p-chloro substitution of
aromatic ring enhances the activity prominently
(CD11, CD30 and CD12, CD29). In general, ester
derivatives are more active than amides. Activity
increases with an increase in length of carbon chain,
whereas branching decreases the activity. When
phenyl ring is flanked by -CH2-, activity enhances
(CD28 and CD29). Fusion of heteroaromatic ring
increases the activity (CD26 and CD29). o-Nitro or
fluoro substitution of anilide diminishes the activity
significantly, whereas meta or para substitution with
nitro or fluoro groups increases it (CD6 ñ CD10,
CD25). Activity is lowered with the replacement of
one aromatic carbon with nitrogen (CD12 ñ CD15).
Dearomatization has diminishing effect on activity
(CD12 and CD19). Hydrazine derivative (CD21)
has the lowest activity. When two heteroatoms are
separated by two carbon chain, the activity
enhances.
In E. coli, some interesting activities are
obtained. p-Nitro anilide derivative (CD25) is most
active followed by o-nitro (CD6) and p-methoxy
(CD24) derivatives. o-Fluoro and 2,5-dimethyl
anilides (CD8 and CD18) and m-amino pyridinyl
(CD14) derivatives exhibit prominent activities.
Ethanolamine and p-chlorophenol derivatives are
least active.
In case of antifungal activities, increasing the
carbon chain length results in higher activities. This
can be seen from activity trends between CD1ñ5 and
16. Branching of the chain does not alter the activity. Activity enhancement by aromatic ring is lower
than by aliphatic ring (CD12 and CD19).
Substitution of aromatic carbons with nitrogen
increases the activity slightly and the position of
substitution does not affect the activity (CD12 and
CD13ñ15). Substitution of aromatic rings with nitro
group at any position increases the activity by the
same magnitude (CD6, 7 and 25). Chloro substitution is better activity enhancer than fluoro substitution (CD8ñ10 and CD11, 30). The derivative con-
Figure 1: Plot of observed pMICbs/sa versus calculated pMICbs/sa for model shown as equation 1
193
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
Table 1. Physicochemical properties of synthesized derivatives of decanoic acid.
Comp.
R
Mol. formula
M.W.
B.p.*/M.p. (OC)
Rf
% yield
CD1
CH3-
C11H22O2
186.29
225ñ228*
0.74
70.0
CD2
C2H5-
C12H24O2
200.31
227ñ230*
0.75
65.4
CD3
C3H7-
C13H26O2
214.34
252ñ255*
0.73
64.6
CD4
(CH3)2CH-
C13H26O2
214.34
242ñ245*
0.71
62.4
CD5
C4H9-
C14H2802
228.37
263ñ266*
0.72
66.3
CD6
o-NO2-Ph-
C16H24N2O3
292.37
65ñ68
0.42
63.8
CD7
m-NO2-Ph-
C16H24N2O3
292.37
82ñ85
0.48
51.7
CD8
o-F-Ph-
C16H24FNO
265.36
58ñ61
0.51
70.8
CD9
m-F-Ph-
C16H24FNO
265.36
78ñ81
0.49
68.6
CD10
p-F-Ph-
C16H24FNO
265.36
82ñ85
0.33
62.9
CD11
p-Cl-Ph-
C16H24ClNO
281.82
162ñ165
0.41
87.7
CD12
Ph-
C16H25NO
247.37
62ñ65
0.78
69.4
CD13
2-Pyr-
C16H24N2O
248.36
60ñ63
0.66
55.6
CD14
3-Pyr-
C16H24N2O
248.36
110ñ113
0.64
67.7
CD15
4-Pyr-
C16H24N2O
248.36
125ñ128
0.67
68.2
CD16
(CH3)2CHCH2-
C14H28O2
228.37
241ñ244*
0.73
63.3
CD17
2,3-Dimethyl-Ph-
C18H29NO
275.42
85ñ88
0.75
69.5
CD18
2,5-Dimethyl-Ph-
C18H29NO
275.42
95ñ98
0.77
70.6
CD19
Cyclohexylamino
C16H31NO
253.42
170ñ173
0.54#
60.0
CD20
OHCH2CH2-
C12H25NO2
215.33
70ñ73
0.25#
55.0
CD21
NH2-
C10H22N2O
186.29
160ñ163
0.82#
58.9
CD22
PhNH-
C16H26N2O
262.39
250ñ253
#
0.83
67.5
CD23
PhCH2-
C17H27NO
261.40
230ñ233
0.85#
67.2
CD24
p-OMe-Ph-
C17H27NO2
277.40
180ñ183
0.73
72.8
CD25
p-NO2-Ph-
C16H24N2O3
292.37
65ñ68
0.42
73.8
CD26
8-Hydroxy quinolinyl
C19H25NO2
299.40
220ñ223
0.87
75.0
CD27
Piperazinyl
C14H28N2O
240.38
200ñ203
0.71#
58.5
CD28
PhCH2-
C17H26O2
262.38
267ñ270*
0.88
65.6
CD29
Ph-
C16H24O2
248.36
195ñ198*
0.86
60.4
CD30
p-Cl-Ph-
C16H23ClO2
282.80
292ñ295*
0.43
63.9
TLC mobile phase: chloroform : toluene (7:3, v/v), chloroform : methanol (7:3, v/v)
#
taining more rings is more active (CD26, most
active). Introduction of methyl group between oxygen atom or ñNH- group and aromatic rings increases the activity (CD12, 29 and CD23, 28).
In order to determine correlations between structural features of synthesized derivatives and their
antimicrobial activity, QSAR studies were undertaken
using the linear free energy relationship mode discussed by Hansch and Fujita (12). Antimicrobial activities determined as MIC were first converted to
ñlogMIC on molar basis and they were used as dependent variables. First, the chemical structures of synthe-
sized compounds were drawn. Then, all the structures
were energy minimized using MM2 and AMI (Austin
Model 1) mode of energy minimization with minimum
RMS (Root Mean Square) gradient of 0.01.
Various descriptors including topological, geometrical, constitutional, electronic, thermodynamic
etc. were calculated for all derivatives. The descriptors used in the present study are Bindx (Balaban
index), ClsC (cluster count), SAS (Connolly accessible area), MS (Connolly molecular area), SEV
(Connolly solvent excluded volume), Vc (critical volume), Diam (diameter), DPLL (dipole length),
194
ASHWANI KUMAR et al.
Table 2. Antimicrobial activity (pMIC µmol/mL) of decanoic acid derivatives.
Compd.
pMICbs/saa
pMICecb
pMICca/anc
CD1
1.474
1.506
1.474
CD2
1.506
1.535
1.506
CD3
1.535
1.836
1.535
CD4
1.526
1.563
1.535
CD5
1.563
1.670
1.563
CD6
1.270
2.215
1.670
CD7
1.557
1.628
1.670
CD8
1.514
2.103
1.628
CD9
1.558
1.628
1.628
CD10
1.558
1.654
1.628
CD11
1.654
1.597
1.654
CD12
1.533
1.599
1.597
CD13
1.486
1.599
1.599
CD14
1.484
2.102
1.599
CD15
1.484
1.563
1.599
CD16
1.560
1.644
1.563
CD17
1.559
1.644
1.644
CD18
1.516
2.106
1.644
CD19
1.519
1.537
1.608
CD20
1.255
1.474
1.537
CD21
1.247
1.623
1.474
CD22
1.480
1.621
1.623
CD23
1.510
1.647
1.621
CD24
1.535
2.215
1.647
CD25
1.557
2.220
1.670
CD26
1.587
1.585
1.680
CD27
1.355
1.623
1.585
CD28
1.599
1.599
1.623
CD29
1.558
1.656
1.599
CD30
1.656
1.474
1.656
Standard
2.61*
2.61*
2.64**
*Ciprofloxacin for B. subtilis/E. coli/S. aureus, **Fluconazole, aB. subtilis/S. aureus; b E. coli; c C. albicans/A. niger
HOMO (HOMO energy), LUMO (LUMO energy),
MR (molecular refractivity), Tindx (molecular topological index), Ovality, ShpA (shape attribute), ClogP
(partition coefficient), Sdeg (sum of degrees), SVDe
(sum of valence degrees), Tcon (total connectivity),
Tot E (total energy), Windx (Wiener index) (13ñ18)
All the above steps were carried out using Chem.
Office 2004 (19). Twenty one descriptors were selected manually and the values of selected descriptors are
presented in Table 3. These descriptors were used as
independent variables in regression analysis. Multiple
linear regression analysis was used to develop QSAR
equations using SPSS 10.05 version. (20)
For generation of linear regression models, set
of 30 compounds (CD1ñCD30) was used. As the
reference drugs, ciprofloxacin and fluconazole,
belong to different structural series, they are not
included in the model development.
438145 20.00 602.80 322.60 277.70 925.50 16.00
549649 21.00 611.70 325.80 276.10 897.50 16.00
442540 22.00 619.00 333.00 287.20 988.50 15.00
196610 17.00 552.40 295.00 259.50 822.50 13.00
350540 19.00 602.00 320.10 268.90 905.50 15.00
264628 18.00 562.70 297.30 253.20 849.50 14.00
341808 19.00 587.50 312.50 267.60 898.50 15.00
CD24
CD25
CD26
CD27
CD28
CD29
CD30
417921 20.00 618.10 335.40 286.10 963.50 14.00
CD17
350540 19.00 598.60 318.50 269.50 907.50 15.00
295145 16.00 568.20 302.30 257.50 839.50 13.00
CD16
350540 19.00 596.70 314.40 260.70 886.50 15.00
264628 18.00 552.30 291.20 247.30 844.50 14.00
CD15
CD23
264628 18.00 552.40 291.30 247.20 844.50 14.00
CD14
CD22
264628 18.00 566.20 296.40 246.80 844.50 14.00
CD13
106775 13.00 452.60 232.50 195.40 652.50 11.00
264628 18.00 561.40 296.90 251.50 851.50 14.00
CD12
CD21
341808 19.00 593.60 315.30 265.30 900.50 15.00
CD11
217483 15.00 524.50 272.30 227.70 754.50 13.00
341808 19.00 575.60 304.10 254.20 869.50 15.00
CD10
CD20
337636 19.00 575.50 304.10 254.10 869.50 14.00
CD9
413549 20.00 599.60 325.80 288.00 963.50 14.00
333359 19.00 574.80 303.80 254.10 869.50 14.00
CD8
264628 18.00 586.70 315.20 282.10 892.50 14.00
534228 21.00 617.20 328.20 277.20 897.50 15.00
CD7
CD19
518512 21.00 604.70 324.30 274.70 907.50 14.00
CD6
CD18
301085 16.00 551.90 296.40 261.50 845.50 14.00
CD5
2.70
2.61
1.65
2.96
3.88
4.72
2.36
3.64
2.62
2.93
4.56
3.64
2.38
3.49
1.76
1.16
1.26
4.16
2.45
4.04
4.05
2.70
1.68
4.21
2.37
1.55
1.36
1.57
1.46
1.53
Cp
LUMO MR
322.30 -0.064 7.520
322.30 -0.136 7.520
322.30 0.149 7.520
325.80 0.181 7.731
341.10 0.052 8.222
336.00 0.096 7.747
336.00 0.114 7.747
336.00 0.086 7.747
367.80 -2.961 8.342
370.90 -1.936 8.317
349.40 1.786 7.825
375.40 0.248 8.659
375.40 0.409 8.659
-9.36
-9.33
-9.52
-9.22
-8.97
-9.21
-8.80
-9.84
-7.99
9187
8477
7739
7653
2612
3905
6508
8258
8343
4810
6392
6404
6416
6508
7154
7154
7097
7040
8968
8636
4910
3942
4034
3274
2622
1.589
1.567
1.579
1.593
1.428
1.510
1.515
1.545
1.597
1.544
1.529
1.529
1.558
1.541
1.579
1.567
1.567
1.566
1.596
1.587
1.499
1.506
1.527
1.496
1.469
343.90 -0.099 8.007
328.70 0.237 7.515
351.60 0.345 7.979
328.00 1.616 7.266
7075
6434
7658
5316
1.556
1.536
1.589
1.499
6.576 17.050
5.723 16.060
6.192 17.050
3.405 15.060
5.986 20.050
5.688 19.050
5.468 18.050
5.182 17.050
4.503 17.050
2.608 11.080
2.827 13.070
5.185 16.060
5.091 18.050
5.691 18.050
5.871 14.060
4.724 16.060
4.724 16.060
4.724 16.060
5.393 16.060
6.364 17.050
5.794 17.050
5.794 17.050
5.194 17.050
5.688 19.050
3.633 19.050
6.001 14.060
5.252 13.070
5.472 13.070
4.943 12.070
4.414 11.080
Tindx Ovality ClogP ShpA
376.00 -0.584 8.992 10294 1.582
367.80 -1.126 8.342
365.70 -0.011 8.348
348.80 0.071 8.195
343.30 0.489 8.100
-10.35 269.50 1.314 5.588
-10.09 307.00 1.607 6.300
-9.88
-8.67
-8.57
-11.08 343.20 1.301 6.859
-9.56
-9.18
-9.06
-8.86
-8.80
-8.71
-8.92
-8.83
-9.02
-9.57
-10.98 342.70 1.255 6.859
-10.78 320.30 1.361 6.396
-11.06 319.80 1.297 6.396
-11.05 296.90 1.291 5.932
-11.17 273.90 1.249 5.468
Diam DPLL HOMO
212665 15.00 535.50 280.70 239.30 783.50 12.00
Vc
CD4
SEV
217483 15.00 544.80 284.30 238.80 789.50 13.00
MS
154027 14.00 511.30 264.80 221.40 733.50 12.00
SAS
CD3
ClsC
CD2
Bindx
106775 13.00 480.70 246.20 204.00 677.50 11.00
CD1
Compd.
Table 3. Values of selected descriptors of decanoic acid derivatives used in linear regression analysis.
38
36
38
34
46
42
40
38
38
24
28
36
40
40
30
36
36
36
36
38
38
38
38
42
42
30
28
28
26
24
54
52
54
44
68
68
58
52
54
34
40
44
54
54
40
52
52
52
50
52
58
58
58
68
67
40
38
38
36
34
Sdeg SVDe
Tcon
0.002
0.003
0.002
0.004
0.0004
0.001
0.002
0.002
0.002
0.026
0.013
0.003
0.002
0.002
0.01
0.003
0.003
0.003
0.003
0.002
0.002
0.002
0.002
0.001
0.001
0.009
0.015
0.013
0.018
0.026
-3381
-3021
-3177
-2914
-3625
-3748
-3397
-3077
-3141
-2319
-2731
-3006
-3233
-3233
-2822
-2986
-2986
-2986
-2921
-3282
-3393
-3393
-3393
-3743
-3750
-2822
-2666
-2666
-2510
-2355
Tot E
958
826
982
688
1328
1262
1109
982
982
346
524
826
1046
1057
622
826
826
826
826
958
958
946
934
1226
1190
635
512
524
428
346
Wind
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
195
0.876
0.372
0.880
0.929
0.873
0.418
0.783
0.886
0.832
0.832
0.810
Vc
Diam
DPLL 0.404
HOMO 0.573
0.911
MS
SEV
0.994
0.912
-0.877
0.923
0.953
0.876
0.899
-0.739 -0.909
Sdeg
SVDe
Tcon
Tot E -0.936 -0.953
Windx 0.934
0.994
0.820
-0.895
1
0.997
0.911
shpA
0.916
0.933
0.571
0.438
0.420
ClogP
0.924
0.879
Ovality 0.851
0.932
0.947
0.977
0.857
MR
Tindx
0.914
-0.863
-0.890
0.799
0.911
0.928
0.562
0.890
0.927
0.951
-0.581
0.975
0.957
-0.611
0.893
Cp
LUMO -0.806 -0.760
0.635
0.354
0.857
0.977
0.977
1
MS
0.648
0.964
0.955
0.995
0.928
0.891
1
1
0.933
0.911
SAS
SAS
ClsC
ClsC
1
Bindx
Bindx
0.951
0.679
0.303
0.844
1
Vc
0.791
0.690
0.415
1
0.312
0.434
1
Diam DPLL
0.786
0.922
0.929
0.570
0.845
0.931
0.969
0.810
0.864
0.873
0.558
0.839
0.877
0.870
0.420
0.419
0.418
-0.021
0.366
0.421
0.401
0.861
0.907
0.877
0.440
-0.801 -0.830 -0.836 -0.439
-0.859 -0.902 -0.880 -0.326
0.719
0.865
0.880
0.534
0.773
0.879
0.921
-0.486 -0.535 -0.602 -0.304
0.976
0.572
0.320
0.802
0.966
1
SEV
Table 4. Correlation matrix for intercorrelation of descriptors.
1
Cp
0.769 -0.873
0.866 -0.742
0.893 -0.760
0.509 -0.255
0.816 -0.682
0.896 -0.746
0.907 -0.648
1
Lumo
0.756
0.887 -0.787
-0.693 -0.844 0.815
-0.781 -0.812 0.566
0.746
0.804
0.783
0.161
0.669
0.769
0.798
-0.512 -0.570
0.546
1
Homo
0.943
0.990
0.994
0.445
0.877
1
0.839
0.860
0.879
0.540
1
1
1
0.349 0.954 0.949
0.424 0.997
0.437
1
Tindx Ovality ClogP shpA Sdeg
0.961
0.995
0.879
0.435 0.994 0.987
-0.883 -0.931 -0.855 -0.424 -0.953 -0.938
-0.925 -0.882 -0.823 -0.454 -0.909 -0.914
0.873
0.978
0.977
0.468
0.860
0.977
1
MR
1
1
0.963 -0.868 -0.959
-0.965 0.827
-0.811
1
1
SVDe Tcon Tot E Windx
196
ASHWANI KUMAR et al.
197
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
Table 5. Correlation between descriptors and pMIC
Descriptor
pMICbs/sa
pMICec
pMICca/an
Bindx
0.310
0.516
0.866
ClsC
0.368
0.417
0.975
SAS
0.500
0.323
0.922
MS
0.488
0.335
0.914
SEV
0.462
0.330
0.864
Vc
0.506
0.327
0.912
Diam
0.506
0.339
0.855
DPLL
-0.036
-0.112
0.372
HOMO
0.184
0.264
0.774
Cp
0.411
0.416
0.860
LUMO
-0.174
-0.410
-0.736
MR
0.418
0.357
0.963
Tindx
0.382
0.407
0.960
Ovality
0.473
0.289
0.873
ClogP
0.973
-0.032
0.505
shpA
0.368
0.417
0.975
Sdeg
0.365
0.388
0.974
SVDe
0.270
0.454
0.917
Tcon
-0.405
-0.314
-0.903
Tot E
-0.328
-0.451
-0.936
Windx
0.364
0.427
0.963
First, a correlation matrix was generated to
study the correlation between descriptors as well as
between descriptors and antimicrobial activity, presented in Table 4 and Table 5. A perusal of Table 4
shows that a majority of parameters is highly intercorrelated except DPLL, HOMO, LUMO and
ClogP. The regression model containing highly correlated parameters together will suffer from the
problem of autocollinearity and such models will
give redundant information (21).
Inspection of Table 5 shows that ClogP is highly correlated with antimicrobial activity against B.
subtilis and S. aureus. The topological (ClsC, ShpA,
Sdeg, Windx, SVde, Tcon), steric ( SAS, MS), thermodynamic (MR, Vc) and electronic (TotE) parameters show very good correlation with antifungal
activity against C. albicans and A. niger . Best models for both above said activities are given in the following equations (1 and 2):.
The QSAR model for antibacterial activity
against B. subtilis/S. aureus
pMICbs/sa =0.1009ClogP +0.988
Eq. 1
N = 30, R = 0.973, R2 = 0.946, F = 500.24, S.E. =
0.024 Q = 41.06, LOO PRESS = 0.0190, LOO pred.
R2 = 0.9359
The QSAR model for antifungal activity
against C. albicans/A. niger
pMICca/an = 0.024835ClsC + 1.152673
Eq. 2
N = 30, R = 0.975, R2 = 0.950, F = 539.5721, S.E. =
0.014 Q = 71.003, LOO PRESS = 0.00606, LOO
pred. R2 = 0.94337
The quality of the models is indicated by the
following parameters: R, correlation coefficient; R2 ,
squared correlation coefficient; F, Fischerís statistics; SE, standard error of estimation; Q, Quality
Factor (R/S.E.); Cross validated regression coefficient LOO pred. R2 and LOO PRESS obtained by
LOO (Leave One Out) approach.
In eq. 1, the positive coefficient of ClogP indicates that it is directly proportional to pMICbs.
ClogP (partition coefficient) is a thermodynamic
parameter and represents the lipophilicity of the molecule. The higher the lipophilicity, the more active is
the molecule, most active derivative has the highest
ClogP value (CD30, CD11) and the least active has
the lowest ClogP value (CD20, CD21) as can be seen
198
ASHWANI KUMAR et al.
Figure 2. Plot of observed pMICca/an versus calculated pMICca/an for model shown as equation 2
Scheme 1. General scheme for synthesis of decanoic acid derivatives
199
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
Table 6. Regression and cross validation parameters for the proposed models.
Sr.
QSAR Model (pMIC = )
No.
N
R
R2
S.E.
Q
PRESS
LOO LOO
Pred. R2 MAE
B. subtilis/ S. aureus
1
-0.00145DPLL+0.10086ClogP+0.992194
30 0.973 0.947 0.024 40.428 0.020
0.933
0.017
2
0.002965HOMO+0.10045clogP+1.018613
30 0.973 0.948 0.024 40.597 0.020
0.932
0.018
3
0.00312DPLL+0.004685HOMO+0.100133ClogP+1.045 30 0.974 0.949 0.024 40.209 0.021
0.930
0.018
C. albicans/ A. niger
1
0.001405SAS + 0.798775
30 0.922 0.851 0.024 38.615 0.019
0.820
0.021
2
0.002267MS + 0.914789
30 0.914 0.836 0.025 36.514 0.020
0.810
0.021
3
0.0023SEV + 1.008825
30 0.864 0.747 0.031 27.811 0.030
0.718
0.026
4
0.000716Vc + 0.986116
30 0.912 0.831 0.025 35.872 0.021
0.809
0.021
5
0.041288Diam + 1.02359
30 0.855 0.731 0.032 26.635 0.032
0.703
0.024
6
0.001916Cp + 0.953403
30 0.860 0.740 0.032 27.257 0.307
0.713
0.025
7
0.063147MR + 1.122953
30 0.963 0.927 0.017 57.432 0.009
0.916
0.014
8
1.280531Ovality ñ 0.37939
30 0.873 0.763 0.030 28.989 0.029
0.728
0.026
9
0.0249221ShpA + 1.199551
30 0.975 0.951 0.014 70.966 0.006
0.943
0.009
10 0.010422Sdeg + 1.229217
30 0.974 0.949 0.014 70.127 0.006
0.940
0.010
11 0.005508Svde + 1.319338
30 0.917 0.842 0.025 37.296 0.020
0.817
0.021
12 - 7.7314Tcon + 1.643532
30 0.903 0.815 0.027 33.922 0.023
0.785
0.022
13 - 0.00015TotE + 1.144171
30 0.936 0.877 0.022 43.101 0.015
0.858
0.019
14 0.00022Windx + 1.411714
30 0.963 0.928 0.017 57.953 0.009
0.916
0.013
in Tables 2 and 3. The sample size allowed us to go
for development of multiparametric models. These
bi- and tri-parametric models are shown in Table 6.
Eq. 2 shows the positive correlation of ClsC
(cluster count) with antifungal activity. ClsC is a
topological steric descriptor. An increase in the
value of cluster count increases the activity. CD26
with ClsC value of 22 is most active whereas CD1
and CD21 with ClsC value of 13 are least active.
This shows that the steric factor is a major contributing factor to the antifungal activity.
Other significant models for antifungal activity
are presented in Table 6.
The predictive power of the models can be
judged from the quality factor Q (R/S.E.)(22). The
highest Q = 41.069 and 71.004 for the models
expressed by eq. 1 and 2, respectively, shows that
they have the highest predictive power. Further confirmation of predictive power was made using Leave
One Out (LOO) cross validation method. Value of
LOO pred.R2 for both the models is very good
(0.9359 and 0.94337 for Eq. 1 and Eq. 2, respectively). Also for the suggested models, the observed and
predicted values are very close to each other as evidenced by low residual values presented in Table 7.
Furthermore, the plots between predicted pMIC and
observed pMIC for both equations shown in Figure
1 and Figure 2 favor the robustness of these models.
This proves that both models have very good ability
of prediction. Moreover, these models have the lowest LOO PRESS values.
No QSAR model for E. coli was found statistically significant. So, these are not discussed here.
In silico ADMET (9) studies of synthesized
derivatives of decanoic acid are presented in Table 8
and Table 9. All the in silico predictions have been
carried out using Pharma Algorithm ADME/Tox
Web Boxes (23).
Bioavailability for most of the compounds lies
between 30 and 70%. CD20 has oral bioavailability
> 70%, CD1ñ5, 16, 26, 28ñ30 have < 30% oral
bioavailability. All the synthesized derivatives have
good caco-2 cell permeability. Also, all the compounds are non-substrate of p-glycoprotein.
Therefore, the reason of low bioavailability of compounds mentioned above may be their very poor
aqueous solubility and hydrolysis by esterases in the
biological system. CD20 has good Caco-2 cell permeability (157.34 ◊ 10-4) and aqueous solubility.
CD1, 2, 4, 6, 8, 12ñ15, 19ñ23 and 27 pass the
200
ASHWANI KUMAR et al.
Table 7. Comparison of observed (Obs.) and predicted (Pred.) antimicrobial activity using best QSAR models.
Compd.
CD1
pMICbs/sa
pMICca/an
Obs.
Pred.
Residual
Obs.
Pred.
Residual
1.474
1.433
0.041
1.474
1.476
-0.002
CD2
1.506
1.487
0.019
1.506
1.500
0.005
CD3
1.535
1.540
-0.005
1.535
1.525
0.010
CD4
1.526
1.518
0.008
1.535
1.525
0.010
CD5
1.563
1.594
-0.031
1.563
1.550
-0.028
CD6
1.270
1.355
-0.085
1.670
1.674
-0.004
CD7
1.557
1.562
-0.005
1.670
1.674
-0.004
CD8
1.514
1.512
0.001
1.628
1.625
0.003
CD9
1.558
1.573
-0.015
1.628
1.625
0.003
CD10
1.558
1.573
-0.015
1.628
1.625
0.003
CD11
1.654
1.630
0.024
1.654
1.625
0.029
CD12
1.533
1.532
0.001
1.597
1.600
-0.003
CD13
1.486
1.465
0.021
1.599
1.600
-0.001
CD14
1.484
1.465
0.019
1.599
1.600
-0.001
CD15
1.484
1.465
0.019
1.599
1.600
-0.001
CD16
1.560
1.580
-0.020
1.563
1.550
0.013
CD17
1.559
1.562
-0.004
1.644
1.649
-0.005
CD18
1.516
1.502
0.014
1.644
1.649
-0.005
CD19
1.519
1.511
0.008
1.608
1.600
0.008
CD20
1.255
1.273
-0.019
1.537
1.525
-0.039
CD21
1.247
1.251
-0.004
1.474
1.476
-0.002
CD22
1.480
1.442
0.037
1.623
1.625
-0.002
CD23
1.510
1.511
-0.001
1.621
1.625
-0.004
CD24
1.535
1.540
-0.005
1.647
1.649
-0.002
CD25
1.557
1.562
-0.005
1.670
1.674
-0.004
CD26
1.587
1.592
-0.005
1.680
1.699
-0.019
CD27
1.355
1.332
0.023
1.585
1.575
0.010
CD28
1.599
1.613
-0.014
1.623
1.625
-0.002
CD29
1.558
1.565
-0.008
1.599
1.600
-0.001
CD30
1.656
1.652
0.004
1.656
1.625
0.031
Lipinski rule of five, which says that a compound
shows poor permeability when it contains more than
5 H-bond donors, more than 10 H-bond acceptors
and molecular weight > 500. Poor dissolution results
when logP is higher than 5. When any of these two
criteria are exceeded, the compound always fails
(24). Furthermore, all compounds have TPSA (total
polar surface area) less than 140. All the derivatives
are passively absorbed through trancellular route.
All synthesized molecules are highly bound to
plasma proteins except CD21 (%PPB = 58.72). A
majority of compounds is neutral (no acid or base
groups), so these molecules mainly bind to lipoproteins and to a lesser extent to albumin. CD13ñ15, 21,
26 and CD27 are weak bases (base pKa < 8.5).
These drugs predominantly bind to α1-acid glycoprotein and albumin. All have moderate values of
volume of distribution (Vd). LogD values for all the
derivatives have been calculated at pH 1.7 (stomach), 4.6 (duodenum), 6.5 (jejunum, ileum), 7.4
(blood), 8.0 (colon). At all pH, logD remains the
same except for weakly basic derivatives CD13ñ15,
21, 26 and CD27. Their absorption will be variable
as they get ionized.
201
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
Table 8. Important ADME properties of decanoic acid and its derivatives.
Compound
logP
Oral
bioavailability
Caco-2 cell
permeability(cm/s)
%
PPBa
Vd (L/Kg)b
Log D
(pH 7.4)
Log Swc
Capric acid
3.49
>70%
20.96x10-6
89.85
0.35
1.00
-3.59
CD1
4.15
<30%
309.40x10-6
95.69
2.22
4.15
-3.81
CD2
4.63
<30%
-6
315.02x10
97.65
2.41
4.63
-3.94
CD3
5.12
<30%
317.72x10-6
98.73
2.61
5.12
-4.11
CD4
4.89
<30%
-6
316.71x10
98.33
2.51
4.89
-4.02
CD5
5.60
<30
318.94x10-6
99.31
3.35
5.60
-4.26
CD6
4.63
30-70%
-6
311.55x10
98.31
2.56
4.63
-4.75
CD7
5.06
30-70%
315.72x10-6
98.98
2.37
5.06
-4.72
CD8
4.84
30-70%
-6
313.93x10
98.53
2.66
4.84
-3.89
CD9
5.35
30-70%
317.30x10-6
99.19
2.77
5.35
-4.31
CD10
5.18
30-70%
-6
316.46x10
99.02
2.68
5.18
-4.59
CD11
5.76
30-70%
318.60x10-6
99.53
3.50
5.76
-4.96
CD12
4.93
30-70%
-6
314.74x10
98.60
2.51
4.93
-4.23
CD13
4.10
30-70%
300.84x10-6
86.75
2.34
4.10
-3.52
CD14
4.07
30-70%
-6
299.95x10
86.01
2.22
4.07
-3.54
CD15
3.92
30-70%
294.41x10-6
85.10
2.16
3.91
-3.55
CD16
5.37
<30%
-6
318.47x10
99.10
2.72
5.37
-4.12
CD17
5.75
30-70%
318.58x10-6
99.52
3.57
5.75
-4.98
CD18
5.75
30-70%
-6
318.58x10
99.52
3.54
5.75
-4.25
CD19
4.91
30-70%
314.57x10-6
98.60
2.44
4.91
-4.16
CD20
2.71
>70%
157.34x10
81.84
1.68
2.70
-3.05
CD21
2.33
30-70%
76.40x10-6
58.72
1.58
2.33
-3.92
CD22
4.30
30-70%
-6
296.55x10
97.26
2.42
4.30
-3.57
CD23
4.81
30-70%
313.64x10-6
98.47
2.52
4.81
-4.94
CD24
5.07
30-70%
-6
315.79x10
98.94
2.55
5.07
-4.57
CD25
5.18
30-70%
316.46x10-6
99.11
2.42
5.18
-4.75
CD26
5.87
<30%
-6
319.32x10
98.17
3.83
5.87
-5.40
CD27
2.80
30-70%
152.40x10-6
95.57
2.55
2.18
-2.10
CD28
5.83
<30%
-6
319.27x10
99.54
4.23
5.83
-5.19
CD29
5.82
<30%
319.26x10-6
99.51
4.07
5.82
-4.33
CD30
6.42
<30%
319.72x10
99.78
4.53
6.42
-4.89
-6
6
a: Plasma protein binding, b: Volume of distribution, c: Log of solubility in water
From Table 9 it follows that CD6, 7, 21, 22, 25
are genotoxic. CD27 is harmful to G.I.T, while compound no. 26, 30 are dangerous to kidney. CD6ñ10,
13ñ15, 17, 18, 25 and 27 are deleterious for lungs.
CD1ñ5, 11, 12, 16, 19, 20, 23, 24, 26, 28ñ30 are non
toxic. CD7, 17 and CD18 are most lethal by i.v.
route. Almost all other have higher LD50.
Overall analysis of above discussed ADMET properties shows that CD12, 19, 20 and CD23 have good
ADMET properties for oral absorption. Although these
compounds were not found to be so active against
microbes, they can be further explored for other activities.
Lipophilicity of CD25 can be decreased by introducing some polar groups like hydroxyls etc. and they
can be further explored for antimicrobial activity.
EXPERIMENTAL
All chemicals used are of Himedia
Laboratories Pvt. Ltd., Mumbai, S. D. Fine
202
ASHWANI KUMAR et al.
Table 9. Toxicity properties of decanoic acid and its derivatives.
Compound
Probability
Probability of effect on
Of +ve
Ames test Blood CVS GIT Kidney Liver Lungs
0.05
LD50 (mg/kg) in mouse
i.p.
Oral
i.v.
s.c.
570
1500
250
1600
LD50 (mg/kg)
in rat
i.p.
oral
Decanoic acid
0.023
0.08
0.08
0.06
0.05
0.04
690 3000
CD1
0.046
0.07
0.46
0.12
0.07
0.03
0.10
790
1700
140
1400
940 4100
CD2
0.055
0.07
0.46
0.11
0.05
0.03
0.09
800
2200
130
1400
950 4300
CD3
0.050
0.10
0.47
0.10
0.29
0.04
0.09
840
2000
110
1400
920 4500
CD4
0.065
0.09
0.46
0.15
0.31
0.05
0.09
730
1600
92
1100
790 4000
CD5
0.038
0.17
0.30
0.09
0.29
0.04
0.08
790
2400
100
1500
950 5000
CD6
0.761
0.21
0.31
0.32
0.12
0.07
0.90
440
1600
70
1300
450 1900
CD7
0.752
0.21
0.32
0.24
0.19
0.08
0.91
220
1300
53
510
240 1300
CD8
0.044
0.13
0.35
0.09
0.18
0.17
0.94
750
1400
110
870
710 2600
600 2300
CD9
0.044
0.13
0.32
0.12
0.24
0.07
0.88
700
1700
92
1800
CD10
0.044
0.18
0.32
0.10
0.23
0.06
0.88
1300
2100
140
1500 1300 3200
CD11
0.074
0.16
0.17
0.10
0.46
0.07
0.21
480
1700
87
950
540 2200
CD12
0.078
0.12
0.24
0.10
0.21
0.06
0.30
570
1600
93
1400
690 2600
CD13
0.059
0.11
0.10
0.17
0.15
0.05
0.52
230
1200
68
580
310 1300
CD14
0.082
0.13
0.13
0.12
0.15
0.05
0.52
370
1300
83
1100
440 1600
CD15
0.134
0.15
0.12
0.17
0.15
0.04
0.52
210
1000
75
410
280 1100
CD16
0.033
0.11
0.46
0.09
0.13
0.04
0.09
690
2200
100
1200
820 4400
CD17
0.178
0.11
0.11
0.12
0.22
0.09
0.68
530
1500
60
1200
540 2800
CD18
0.154
0.07
0.14
0.12
0.19
0.08
0.68
510
1300
54
990
390 2300
CD19
0.009
0.26
0.16
0.14
0.30
0.19
0.25
540
1400
77
850
670 3100
CD20
0.041
0.14
0.20
0.05
0.06
0.09
0.05
1100
2200
200
1900 1000 4200
CD21
0.556
0.40
0.34
0.24
0.11
0.15
0.15
330
1100
87
440
270 1700
CD22
0.527
0.35
0.26
0.14
0.11
0.12
0.40
310
1100
110
520
240 1500
CD23
0.085
0.18
0.16
0.12
0.40
0.07
0.36
570
570
1500
1100 1000 3100
CD24
0.112
0.23
0.19
0.05
0.20
0.04
0.33
850
850
2200
1600 1000 3500
CD25
0.761
0.23
0.41
0.24
0.19
0.07
0.91
440
440
1700
710
450 1800
CD26
0.335
0.42
0.24
0.27
0.52
0.12
0.30
660
660
1700
1200
740 2200
CD27
0.011
0.37
0.35
0.74
0.21
0.19
0.72
190
190
830
560
160 1500
CD28
0.052
0.07
0.48
0.16
0.12
0.04
0.41
520
520
1600
1100
630 3200
CD29
0.042
0.22
0.31
0.12
0.17
0.02
0.35
820
820
1700
1600
860 2900
CD30
0.041
0.25
0.33
0.13
0.69
0.03
0.32
660
660
1700
1500
580 2600
Chemicals Ltd., Mumbai and Sisco Research
Laboratories Pvt. Ltd., Mumbai.
All the melting and boiling points given in this
study are uncorrected. The IR spectra of compounds
were recorded on Perkin Elmer IR Spectrophotometer using KBr discs. IR spectra of liquids were
recorded as neat liquids. The NMR spectra of compounds are recorded on Bruker Avance II 400 NMR
spectrometer using CDCl3 as a solvent and TMS as
an internal standard. Thin layer chromatography was
done with silica gel G as adsorbent and spots are
visualized by exposure to iodine vapors and it is used
as a basis of purity. C, H, N analysis was carried out
using Carlo Erba 1106 CHN analyzer.
Chemistry
General procedure for synthesis of ester derivatives of decanoic acid (CD1ñ5, 16, 28)
A mixture of decanoic acid (0.1 mol) and
appropriate alcohol (0.9 mol) was heated under
Synthesis, antimicrobial evaluation, QSAR and in silico ADMET...
reflux in the presence of sulfuric acid till the completion of reaction checked by TLC. Once the reaction has been completed, the reaction mixture was
added to 200 mL of ice cold water and the ester
formed was extracted with diethyl ether (50 mL).
The ether layer was separated and on evaporation
yielded the crude ester derivatives of capric acid.
The crude product was recrystallized from etanol.
General procedure of preparation of phenolic
ester derivatives of decanoic acid (CDñ26, 29ñ30)
A solution of 8-hydroxyquinoline or phenol or
4-chlorophenol (0.05 mol) in diethyl ether (50 mL)
was added to a solution of decanoyl chloride (0.05
mol) in diethyl ether (50 mL). The mixture was
heated until no further evolution of hydrogen chloride was observed and completion of reaction was
checked by TLC. The mixture was cooled down to
room temperature and on evaporation of solvent,
solid product of 8-hydroxyquinoline and liquid
products of phenol/4-chlorophenol was obtained.
They were purified by recrystallization from etanol.
General procedure for synthesis of amide/anilide
derivatives of decanoic acid (CD6ñ15, 17ñ25, 27)
(25)
The acid chloride of decanoic acid was prepared by reaction of decanoic acid with thionyl chloride. The solution of corresponding amine (0.1 mol)
in diethyl ether (50 mL) was added dropwise to a
solution of acid chloride (0.1 mol) in diethyl ether
(50 mL) maintained at 0ñ10OC/room temperature.
The solution was stirred for 30 min and the precipitated amide was separated by filtration. The crude
amide was recrystallized from etanol. In case of
anilides, the precipitated crude anilide was treated
with 5% hydrochloric acid, 4% sodium carbonate
and water to remove residual aniline and the resultant anilide was recrystallized from etanol.
The hydrazide derivative CD-21 was prepared
by refluxing methyl decanoate (0.1 mol) with
hydrazine hydrate (0.2 mol) for 2 h. The resulting
mixture was cooled down to room temperature and
the solid separated was filtered, washed with water
and recrystallized from etanol.
The structures of the synthesized compounds
were characterized by spectral analysis. Analytical
data for selected compounds are given below:
Methyl decanoate (CD-1)
1
H-NMR (δ, ppm): 0.90ñ0.86 (t, J = 6.8 Hz,
CH3, 3H), 1.30ñ1.23 (m, (CH2)6, 12H), 1.64ñ1.60
(m, CH2, 2H), 2.32ñ2.28 (t, J = 7.6 Hz, CH2, 2H),
3.66 (s, CH3, 3H). IR (cm-1): 2928.0 (C-H, aliphatic),
203
2854.3 (C-H, aliphatic), 1741.7 (C=O, aliphatic
ester), 722.9 (CH2 aliphatic). Analysis: calcd. for
C11H22O2: C, 70.92; H, 11.90%; found: C, 70.79; H,
12.13%.
Ethyl decanoate (CD-2)
1
H-NMR (δ, ppm): 0.90ñ0.86 (t, J = 6.8 Hz,
CH3, 3H), 1.41ñ1.20 (m, (CH2)6, CH3, 15H),
1.66ñ1.58 (m, CH2, 2H), 2.31ñ2.26 (t, J = 7.4 Hz,
CH2, 2H), 4.15ñ4.09 (q, J = 7.2 Hz, CH2, 2H). IR
(cm-1): 2924.9 (C-H, aliphatic), 2854.6 (C-H,
aliphatic), 1737.9 (C=O, aliphatic ester), 722.9 (CH2
aliphatic). Analysis: calcd. for C12H24O2: C, 71.95;
H, 12.08%; found: C, 72.19; H, 11.87%.
N-(3-fluorophenyl) decanamide (CD-9)
1
H-NMR (δ, ppm): 0.89ñ0.85 (t, J = 6.8 Hz,
CH3, 3H), 1.30ñ1.25 (m, (CH2)6, 12H), 1.73ñ1.61
(m, CH2, 2H), 2.37ñ2.32 (t, J = 7.6 Hz, CH2, 2H),
6.77 (s, NH, 1H), 7.15ñ7.26 (m, Ar-H, 4H). IR (cm-1):
3312.11 (N-H), 3033.68 (Ar-H), 2924ñ2850.55
(C-H), 1670 (C=O), 1607.05ñ1522.05 (C=C),
1191.86 (C-F), 776.69 [=C-H (OOP)], 725.62 (CH2
aliphatic). Analysis: calcd. for C16H24OFN: C,
74.42; H, 9.12; N, 5.28%; found: C, 74.59; H, 8.97;
N, 5.37%.
N-phenyl decanamide (CD-12)
1
H-NMR (δ, ppm): 0.89ñ0.86 (t, J = 6.8 Hz,
CH3, 3H), 1.31ñ1.26 (m, (CH2)6, 12H), 1.73ñ1.63
(m, CH2, 2H), 2.37ñ2.32 (t, J = 7.6 Hz, CH2, 2H),
5.49 (s, NH, 1H), 7.52ñ7.06 (m, Ar-H, 5H). IR (cm-1):
3305 (N-H), 3044.05 (Ar-H), 2917.96 (C-H),
2850.26 (C-H), 1656.46 (C=O), 1600 (C=C aromatic), 755.18 [=C-H (OOP)], 726.98 (CH2 aliphatic).
Analysis: calcd. for C16H25NO: C, 77.68; H, 10.19;
N, 5.66%; found: C, 77.43; H, 10.33; N, 5.75%.
N-Cyclohexyl decanamide (CD-19)
1
H-NMR (δ, ppm): 0.89ñ0.88 (t, J = 6.8 Hz,
CH3, 3H), 1.92ñ1.06 (m, (CH2)12, 24H), 2.17ñ2.11
(t, J = 7.6 Hz, CH2, 2H), 3.78ñ3.72 (t, J = 7.2 Hz,
CH, 1H), 5.35 (s, NH, 1H). IR (cm-1): 3300.37 (N-H),
2930.28 (C-H), 2852.66 (C-H), 1639.19 (C=O),
720.68 (CH2 aliphatic). Analysis: calcd. for
C16H31NO: C, 75.83; H, 12.33; N, 5.53%; found: C,
75.91; H, 12.58; N, 5.69%.
N-Benzyl decanamide (CD-23)
1
H-NMR (δ, ppm): 0.89ñ0.86 (t, J = 6.8 Hz,
CH3, 3H), 1.33ñ1.23 (m, (CH2)6, 12H), 1.68ñ1.61
(m, (CH2), 2H), 2.22ñ2.16 (t, J = 7.6 Hz, CH2, 2H),
4.44 (s, CH2, 2H), 5.8 (s, N-H, 1H), 7.35ñ7.25 (m,
Ar-H, 5H). IR (cm-1): 3293.50 (N-H), 3032 (Ar-H,
204
ASHWANI KUMAR et al.
aromatic), 2917.77 (C-H), 2849.43 (C-H), 1633.39
(C=O), 748.52 (=C-H OOP), 724.12 (CH2), 695.40
(monosubst. ring). Analysis: calcd. for C17H27NO:
C, 78.11; H, 10.41; N, 5.36%; found: C, 78.32; H,
10.53; N, 5.55%.
Biology
Antibacterial assay
The antibacterial activity of synthesized
decanoic acid derivatives against the bacterial
strains S. aureus, B. subtilis and E. coli was determined by serial dilution method using nutrient broth
IP. The inoculated tubes were incubated at 37 ± 1OC
for 24 h for all the three strains of bacteria. From the
stock solution, further dilutions were made to get
concentration from 50 to 3.12 µg/mL in the tube
containing 1 mL of sterile double strength broth IP.
The tubes were inoculated with 100 µL of suspension of organisms (B. subtilis, S. aureus and E. coli)
in sterile saline. These tubes were incubated at 37 ±
1OC for 24 h and minimum inhibitory concentrations
(MIC) were determined. By observing MIC values,
the exact MIC values were determined by making
suitable dilution of stock solution.
Antifungal assay
Serial dilution method similar to described
above using Sabouraud dextrose broth IP was used
for the antifungal activity of synthesized decanoic
acid derivatives against the fungal species C. albicans and A. niger. After inoculation, the tubes were
incubated at 37 ± 1OC and 25 ± 1OC for a period of
2 and 7 days in case of C. albicans and A. niger,
respectively.
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Received: 19. 01. 2010